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Purpose of agent-based modeling is to understand or anticipate the behavior of (semi-)autonomous beings acting –individually or collectively, –dependently or independently, –within or outside a real or simulated environment Agent-based simulation involves the use of agents within a real or simulated environment Any agent-based simulation is a theory that encompasses agents, the environment and interactions among them. Foner (1993). "What's An Agent, Anyway?" MIT Agents Report 93-01, Cambridge, MA. Agent-based Modeling and Simulation

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A model is only useful to the extent that it is valid. Today I will talk about models of cognition, expressed as agents, and a bit about models of the environments with which they interact. The bulk of my time will be devoted to a discussion of how to develop and validate models of cognition expressed as agents. Today

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"Methods that produce detailed models of how humans perform complex cognitive tasks that can be run on a computer. Such models can provide a priori performance predictions of how well a certain system will support the tasks workers perform by assessing factors such as how easy the system will be to learn and use, the workload it imposes, and the propensity for errors. Software agents that perform work tasks in the same way that humans perform work tasks can be used to evaluate proposed system designs without the need to conduct these types of evaluations with actual workers. The downside to these methods is that they can be time-consuming and, with the exception of GOMS, have not yet seen widespread use in the engineering community."

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Validation based on Outcomes Given (i) some prior set of decisions and (ii) a mix of feasible resources at time t, to what extent do the model’s choices at time (t+1) match the group’s choices? Interval Size

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Validation based on Outcomes For the session as a whole, to what extent do resource:goal pairings from the model match those of the group? Case12 Goal Rolex CA FD MO PD AR

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Validation based on Processes Given (i) some prior set of decisions and (ii) mix of feasible resources at time t, to what extent do the model’s decision processes match those of the group?

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Validation Redux Decide at onset on where model validation will take place –Outcome –Process –Both What are the corresponding data needs? What are the rejection criteria?

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Summary Complex, dynamic interactions are the rule in management and restoration of critical infrastructures. Analytic tools for increasing understanding and informing design are insufficient for generating understanding of these systems. Agent-based simulation is one tool for doing so: –extremely detailed descriptions of both human and machine cognition and behavior are possible –many avenues for conducting validation The resulting simulation models are themselves infrastructure that, with proper maintenance, will provide returns on investment not available from one-shot studies.